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IMPI: Making MPI Interoperable.

ABSTRACT: The Message Passing Interface (MPI) is the de facto standard for writing parallel scientific applications in the message passing programming paradigm. Implementations of MPI were not designed to interoperate, thereby limiting the environments in which parallel jobs could be run. We briefly describe a set of protocols, designed by a steering committee of current implementors of MPI, that enable two or more implementations of MPI to interoperate within a single application. Specifically, we introduce the set of protocols collectively called Interoperable MPI (IMPI). These protocols make use of novel techniques to handle difficult requirements such as maintaining interoperability among all IMPI implementations while also allowing for the independent evolution of the collective communication algorithms used in IMPI. Our contribution to this effort has been as a facilitator for meetings, editor of the IMPI Specification document, and as an early testbed for implementations of IMPI. This testbed is in the form of an IMPI conformance tester, a system that can verify the correct operation of an IMPI-enabled version of MPI.

SUBMITTER: George WL

PROVIDER: S-EPMC4874770 | biostudies-literature | 2000 May-Jun

REPOSITORIES: biostudies-literature

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IMPI: Making MPI Interoperable.

George W L WL Hagedorn J G JG Devaney J E JE

Journal of research of the National Institute of Standards and Technology 20000501 3

The Message Passing Interface (MPI) is the de facto standard for writing parallel scientific applications in the message passing programming paradigm. Implementations of MPI were not designed to interoperate, thereby limiting the environments in which parallel jobs could be run. We briefly describe a set of protocols, designed by a steering committee of current implementors of MPI, that enable two or more implementations of MPI to interoperate within a single application. Specifically, we introd ...[more]

PMID: 27551614

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Project description:The progress of next-generation sequencing has lead to the availability of massive data sets used by a wide range of applications in biology and medicine. This has sparked significant interest in using modern Big Data technologies to process this large amount of information in distributed memory clusters of commodity hardware. Several approaches based on solutions such as Apache Hadoop or Apache Spark, have been proposed. These solutions allow developers to focus on the problem while the need to deal with low level details, such as data distribution schemes or communication patterns among processing nodes, can be ignored. However, performance and scalability are also of high importance when dealing with increasing problems sizes, making in this way the usage of High Performance Computing (HPC) technologies such as the message passing interface (MPI) a promising alternative. Recently, MetaCacheSpark, an Apache Spark based software for detection and quantification of species composition in food samples has been proposed. This tool can be used to analyze high throughput sequencing data sets of metagenomic DNA and allows for dealing with large-scale collections of complex eukaryotic and bacterial reference genome. In this work, we propose MetaCache-MPI, a fast and memory efficient solution for computing clusters which is based on MPI instead of Apache Spark. In order to evaluate its performance a comparison is performed between the original single CPU version of MetaCache, the Spark version and the MPI version we are introducing. Results show that for 32 processes, MetaCache-MPI is 1.65× faster while consuming 48.12% of the RAM memory used by Spark for building a metagenomics database. For querying this database, also with 32 processes, the MPI version is 3.11× faster, while using 55.56% of the memory used by Spark. We conclude that the new MetaCache-MPI version is faster in both building and querying the database and uses less RAM memory, when compared with MetaCacheSpark, while keeping the accuracy of the original implementation.

Project description:BACKGROUND:Consistency of results between different readers is an important issue in medical imaging, as it affects portability of results between institutions and may affect patient care. The International Atomic Energy Agency (IAEA) in pursuing its mission of fostering peaceful applications of nuclear technologies has supported several training activities in the field of nuclear cardiology (NC) and SPECT myocardial perfusion imaging (MPI) in particular. The aim of this study was to verify the outcome of those activities through an international clinical audit on MPI where participants were requested to report on studies distributed from a core lab. METHODS:The study was run in two phases: in phase 1, SPECT MPI studies were distributed as raw data and full processing was requested as per local practice. In phase 2, images from studies pre-processed at the core lab were distributed. Data to be reported included summed stress score (SSS); summed rest score (SRS); summed difference score (SDS); left ventricular (LV) ejection fraction (EF) and end- diastolic volume (EDV). Qualitative appraisals included the assessment of perfusion and presence of ischemia, scar or mixed patterns, presence of transient ischemic dilation (TID), and risk for cardiac events (CE). Twenty-four previous trainees from low- and middle-income countries participated (core participants group) and their results were assessed for inter-observer variability in each of the two phases, and for changes between phases. The same evaluations were performed for a group of eleven international experts (experts group). Results were also compared between the groups. RESULTS:Expert readers showed an excellent level of agreement for all parameters in both phase 1 and 2. For core participants, the concordance of all parameters in phase 1 was rated as good to excellent. Two parameters which were re-evaluated in phase 2, namely SSS and SRS, showed an increased level of concordance, up to excellent in both cases. Reporting of categorical variables by expert readers remained almost unchanged between the two phases, while core participants showed an increase in phase 2. Finally, pooled LVEF values did not show a significant difference between core participants and experts. However, significant differences were found between LVEF values obtained using different software packages for cardiac analysis. CONCLUSIONS:In this study, inter-observer agreement was moderate-to-good for core group readers and good-to-excellent for expert readers. The quality of reporting is affected by the quality of processing. These results confirm the important role of the IAEA training activities in improving imaging in low- and middle-income countries.

Dataset Information

IMPI: Making MPI Interoperable.

Publications

IMPI: Making MPI Interoperable.

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